34 results about "Spatial data mining" patented technology

Systems and methods are provided for knowledge discovery in spatial data as well as to systems and methods for optimizing recipes used in spatial environments such as may be found in precision agriculture. A spatial data analysis and modeling module is provided which allows users to interactively and flexibly analyze and mine spatial data. The spatial data analysis and modeling module applies spatial data mining algorithms through a number of steps. The data loading and generation module obtains or generates spatial data and allows for basic partitioning. The inspection module provides basic statistical analysis. The preprocessing module smoothes and cleans the data and allows for basic manipulation of the data. The partitioning module provides for more advanced data partitioning. The prediction module applies regression and classification algorithms on the spatial data. The integration module enhances prediction methods by combining and integrating models. The recommendation module provides the user with site-specific recommendations as to how to optimize a recipe for a spatial environment such as a fertilizer recipe for an agricultural field.

The invention provides an urban disaster thematic map real-time generating method based on network information. The method comprises the following steps that S1, the urban disaster information is obtained from networks in real time; S2, the urban disaster information is subjected to automatic place name recognition and is then subjected to spatial orientation; S3, the semantic mapping technology based on space time correlation rules is applied, and the urban disaster information subjected to the spatial orientation is subjected to semantic parsing; S4, the urban disaster information subjected to the semantic parsing is subjected to spatial data mining with graphic correlation, and the urban disaster thematic data with graphic spatial correlation is generated; S5, the urban disaster thematic data are subjected to visual representation, and an urban disaster thematic map is generated. The urban disaster thematic map real-time generating method has the advantages that the urban disaster information can be obtained in real time, the obtained urban disaster information is subjected to intelligent mining, the urban disaster thematic map is quickly generated and dynamically issued, and the quick generation and dynamical issuing level of the urban disaster thematic map is improved, and service is provided for urban management and emergency relief.

The invention discloses a data mining-based drought monitoring method. The method comprises the following steps: 1, data reconstruction is carried out on an MODIS vegetation index product, a land surface temperature product and an evapotranspiration product; 2, according to the vegetation index obtained in the first step and DEM data, downscaling is carried out on a TRMM rainfall product; 3, a vegetation anomaly index, a temperature anomaly index, an evapotranspiration anomaly index and a rainfall anomaly index are extracted again; and 4, a classification and regression tree model is used for building a statistical regression rule and a linear fitting model to obtain a drought monitoring model. Compared with the prior art, the method of the invention comprehensively considers multi-source remote sensing spatial information, such as the rainfall, the evapotranspiration, the vegetation growth state, the land using type, the altitude and other factors, in the case of drought monitoring, spatial data mining is adopted, the drought monitoring model is built, and the drought monitoring precision is improved.

An adaptive traffic control subarea dividing method based on spatial data mining belongs to the field of traffic technology. The method aims to settle a problem of relatively low outgoing efficiency of a control area which is divided by an existing control subarea dividing method. The method comprises the steps of firstly performing characteristic extraction on a peak time period, a valley time period, a high flow threshold, a middle flow threshold and a low flow threshold, selecting a traffic information characteristic which affects dividing of the control subarea; then establishing an influence weight calculating model based on a time-space characteristic, obtaining the weight of a characteristic r, and finally realizing traffic control subarea based on a weighted commodity detection algorithm divided by a dynamic module degree. The adaptive traffic control subarea dividing method is suitable for dividing the traffic control subarea.

It is one object of the present invention to perform regional optimization while taking spatial continuity into account, and to provide higher-level spatial data mining. A region calculation method for introducing a two-dimensional association rule, extracted from a database, that includes spatial information, such as addresses, and for applying the two-dimensional association rule for a map, comprises the steps of: defining an objective function that is used to introduce the two-dimensional association rule and that does not include regional information for which an output request has been submitted; dividing a region on the map into w pixel grids having a predetermined size to form buckets (S101); aggregating data available in the database for each bucket (S103); employing the objective function to calculate a region for the optimization of the objective function (S104); extracting entities, appearing on the map, that correspond to the obtained region (S106); and employing the extracted entities to output a region that is applied for the map.

The invention provides a spatial clustering mining PSE (Problem Solving Environments) system, which comprises a data layer, a functional layer and a user layer, wherein the data layer comprises at least one spatial database for providing basic spatial data; the functional layer is used for packaging a spatial clustering mining module and providing a uniform interface to realize the issuance, the discovery and the call of spatial clustering module service, and is used for visually displaying and returning a spatial clustering analysis result; and the user layer is used for providing the interface for a user to input parameters and select the module service. According to the invention, the spatial clustering mining module is constructed, and an OGC WPS (Web Processing Service) standard is utilized to package the mining module service, so that service sharing is realized on any system and application platform; and a portal architecture is applied, so that the expandability is good, effective support is provided for the discovery and the extraction of data useful in a decision-making process from massive data related to positions, and the application hierarchy and quality of the spatial data mining module is greatly improved and broadened.

The invention discloses an excavating method based on air activity target data, relating to the association and sequence algorithm excavating technology in the data excavating application field. The invention takes the conventional type data excavating method as basis, the spatial data excavating technology is infused, the whole excavating flow and policy from air activity target data preprocessing, statistic analysis, excavating data extracting to result knowledge excavating is completed, and air activity target data excavating is completed. The invention also has the advantages that the method can be applicable to various activity target data excavation, comparison with real time data trend can be carried out by excavation and predicting is carried out on the air target activity. The invention is especially applicable to searching unknown air target activity information in air activity target data accumulated for a long time by computer assist and improves engineering application decision making ability.

A spatial data mining apparatus for calculating an optimal distance from a database, wherein spatial information, such as addresses, is stored, includes an input mechanism, for the input of an objective function required for the optimization of a distance, an intermediate table generator 30, for employing in the database starting point data and query point data for calculating the distances between each starting point and each query point and for generating an intermediate table, and an optimal distance calculator for calculating a distance based on the intermediate table generated by the intermediate table generator, in order to optimize the value of the objective function that is entered by the input mechanism.

The invention belongs to the technical field of information data processing, and provides a temporally and spatially regular subway passenger clustering and edge detecting method. The temporally and spatially regular subway passenger clustering and edge detecting method includes steps of S1, acquiring detailed information of temporal-spatial regulation of temporally and spatially regular subway passengers from source data which contain all riding records of the passengers; S2, clustering the temporally and spatially regular subway passengers according to the acquired detailed information of the temporal-spatial regulation; S3, performing edge detection on the clustered temporally and spatially regular subway passengers and analyzing edge features of the clustered temporally and spatially regular subway passengers. The temporally and spatially regular subway passenger clustering and edge detecting method has the advantages that subway passengers are classified on the basis of temporal-spatial data mining, the temporally and spatially regular passengers are clustered according to the quantities of regular time frames of the temporally and spatially regular passengers, and each class of temporally and spatially regular passengers are analyzed and are subjected to edge detection, so that life features of the passengers can be effectively comprehended.

The invention relates to an uncertainty spatial data mining-based regional metallogenic prediction method, and belongs to the technical field of resource information processing and application. The regional metallogenic prediction method makes full use of multi-source mass geological space data (basic geological mineral data, remote sensing prospecting data, geochemical data and mineral deposit data) and effectively extracts regional metallogenic associated information to perform rapid and effective regional metallogenic prediction based on an uncertainty spatial data mining algorithmic model. The regional metallogenic prediction method comprises three main steps of geometrically registering multi-source and multi-scale geological space data, extracting remote sensing mineralizing information and performing metallogenic prediction based on the uncertainty spatial data mining algorithmic model. The method can evaluate a regional metallogenic prospective area more rapidly and objectively.

The invention provides a spatial data intelligent distribution service method based on big data. The invention relates to the field of spatial data distribution service. The method comprises the stepsof user spatial data collection and order information collection. Statistical analysis is carried out on personal information and behaviors of a user, so that user behavior portrait can be performed,a big data technology is used for carrying out user-to-spatial data content similarity calculation on information such as types and resolutions of spatial data ordered by users and carrying out user-to-user similarity calculation on information such as cities and industries where the users ordering the spatial data are located. and spatial data mining and potential user mining which are interested in the user are realized, and the mined spatial data are intelligently pushed to the user. According to the invention, the user information portrait is established according to the differentiated and dynamic demands of different users on the spatial data, so that intelligent analysis, intelligent acquisition, intelligent classification and intelligent distribution for the spatial data demand ofa specific user are realized, and the construction of an intelligent active push service mode of brand new spatial data distribution is facilitated.

The invention defines a method for auxiliary address selecting of power facilities in a space by utilizing a three-dimensional geological information system. Before the practical layout and address selecting is carried out for the power facilities, such as electric wire poles, firstly, one or a plurality of optimum address selecting schemes are obtained, and are displayed in the three-dimensional geological information system, and then a result is visually displayed for a user. The real, reliable, visual and scientific result is provided for the practical wire selecting and address selecting work of final related workers, the working efficiency is greatly improved, and the workload and the cost of the on-site measurement are reduced.

The invention discloses a spectrum attribute information and space information based reservoir water body classification method. According to the method, spectral clustering is introduced to reservoir water body classification for the first time, a spectrum weight matrix is built by fully utilizing remote-sensing imaging of the spectrum attribute information and space information of the reservoir water body, and the built spectrum weight matrix is regarded as a similarity matrix of a spectral clustering matrix. Therefore, information quality of spatial analysis and spatial data mining can be improved in a better manner, and the accuracy of reservoir water body classification is accordingly and efficiently improved. The invention also discloses a spectrum attribute information and space information based reservoir water body classification device.

The invention discloses a spatial clustering method based on a GACUC (greedy agglomerate category utility clustering) and Delaunay triangulation network. Clustering is performed according to spatial attribution and non spatial attribution of spatial data, the maximum similarities of the non spatial attribution exist among spatial elements in each cluster, and the spatial accessibility of the spatial elements is provided. The non spatial attribution clustering is performed by the GACUC (), the non spatial attribution clustering of non numeric type attribute items can be supported, and the application range of the clustering method is expanded; meanwhile, spatial attribution clustering is performed on the basis of the Delaunay triangulation network, the inherent spatial data and non spatial attribution clustering of the spatial data can be implemented, and correspondence and distribution regularities among the spatial elements can be extracted more accurately. The method is simple to implement, automatic computer processing is adopted, data processing and analyzing time is saved, accuracy and availability of the clustering result are improved, and the method has a board application prospect in the field of spatial data extraction.

The invention discloses a spatial big data mining system based on clustering. The system comprises a data access module, a clustering module, a user interaction module and a knowledge base managementmodule, wherein the data access module is responsible for providing a data access function, can be used as a data access interface of the clustering module and the user interaction module, and completes access to heterogeneous and heterogeneous data in a spatial database at the same time; the clustering module is responsible for receiving and analyzing a data mining task request of the user interaction module, obtaining corresponding data through the data access module and completing clustering analysis, and finally transmitting a corresponding model back to the user interaction module; the user interaction module is responsible for helping a user to complete the interaction process of selecting a data mining algorithm, modeling, loading training data and completing prediction; and the knowledge base management module provides a transparent interface between the clustering module and the user interaction module and provides powerful support for spatial decision.

The invention belongs to the technical field of GPS spatial data mining. Nine derived variables 0-1 are added for each piece of GPS record data, and value assignment is performed according to a changequantity of two pieces of continuous GPS data of the same vehicle. The processing steps after the value assignment are as follows: 1, grid division is performed on a WGS84 coordinate plane; 2, a digital road diagram in a target area is generated; 3, horizontal/vertical adjacent road grids are considered as one road section and a sampled population; 4, statistics is performed on times of enablingvalues of the derived variables 0-1 in the GPS record data to be 1 according to road sections; and 5, according to the road sections, if the acceleration times/the total times are greater than or equal to 0.75, the road section is determined as an acceleration section, and others are deduced by analogy.